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arXiv · 2609.00114

Reconciling Galactic rotation curve constraints with stellar stream modeling

Abstract

Recent Gaia-based measurements of the Milky Way rotation curve and stellar-stream modeling give significantly different estimates of the Galactic dynamical mass beyond Galactocentric radii of 15 kpc. The stream-based model predicts an outer halo five times more massive than that predicted by the Gaia rotation curve. We aim to test the impact of analytic assumptions used in stream modeling and to assess whether the currently available stream constraints can distinguish between low- and high-mass Galactic potentials. We first compared globular-cluster disruption in analytic and N-body Milky Way potentials. We then modeled Palomar~5 and ATLAS--Aliqa Uma, which are unique in probing the outer region beyond $R_{GC}$=15 kpc and are the most relevant to understanding the mass discrepancy. Both streams have usable constraints on sky position, proper motion, line-of-sight velocity, and RR~Lyrae distance. They were modeled for both a rotation-curve-based and a stream-based Galactic potential. In the N-body simulations, tidal shocks have a stronger effect on the closer orbit than on the more distant orbit, and therefore do not naturally explain the outer-Galaxy mass discrepancy. For the streams Palomar 5 and ATLAS--Aliqa Uma, simulations performed for both low- and high-mass Galactic potentials provide comparably good fits of their morphologies and kinematics. Neither potential provides a uniformly better match to all observables, and their differences are comparable to the present observational and modeling uncertainties. Current stream data do not discriminate between the low- and high-mass Milky Way models over the radial range probed by Palomar~5 and ATLAS--Aliqa Uma. This resolves the apparent tension between the rotation-curve- and stream-based constraints over this radial range.

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BibTeXRIS

Mingyu Chang, Francois Hammer, Yanbin Yang. 2026-08-31. Reconciling Galactic rotation curve constraints with stellar stream modeling. https://arxiv.org/abs/2609.00114

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